code: def test_smbo_metalearning_configurations(
      backend, context, dask_client
  ) -> None:
      # Get the inputs to the optimizer
      X_train, Y_train, X_test, Y_test = putil.get_dataset("iris")
      config_space = AutoML(
          delete_tmp_folder_after_terminate=False,
          metrics=[autosklearn.metrics.accuracy],
          time_left_for_this_task=20,
          per_run_time_limit=5,
      ).fit(
          X_train,
          Y_train,
          task=BINARY_CLASSIFICATION,
          only_return_configuration_space=True,
      )
      stopwatch = StopWatch()
  
      # Create an optimizer
      smbo = AutoMLSMBO(
          config_space=config_space,
          dataset_name="iris",
          backend=backend,
          total_walltime_limit=10,
          func_eval_time_limit=5,
          memory_limit=4096,
          metrics=[autosklearn.metrics.accuracy],
          stopwatch=stopwatch,
          n_jobs=1,
          dask_client=dask_client,
          port=logging.handlers.DEFAULT_TCP_LOGGING_PORT,
          start_num_run=1,
          data_memory_limit=None,
          num_metalearning_cfgs=25,
          pynisher_context=context,
      )
      assert smbo.pynisher_context == context
  
      # Create the inputs to metalearning
      datamanager = XYDataManager(
          X_train,
          Y_train,
          X_test,
          Y_test,
          task=BINARY_CLASSIFICATION,
          dataset_name="iris",
          feat_type={i: "numerical" for i in range(X_train.shape[1])},
      )
      backend.save_datamanager(datamanager)
      smbo.task = BINARY_CLASSIFICATION
      smbo.reset_data_manager()
      metalearning_configurations = smbo.get_metalearning_suggestions()
  
      # We should have 25 metalearning configurations
      assert len(metalearning_configurations) == 25
      assert [
          isinstance(config, Configuration)
          for config in metalearning_configurations
      ]
  
file_path: auto-sklearn/test/test_optimizer/test_smbo.py
imports: import logging.handlers
  from ConfigSpace.configuration_space import Configuration
  import autosklearn.metrics
  import autosklearn.pipeline.util
  from autosklearn.automl import AutoML
  from autosklearn.constants import BINARY_CLASSIFICATION
  from autosklearn.data.xy_data_manager import XYDataManager
  from autosklearn.smbo import AutoMLSMBO
  from autosklearn.util.stopwatch import StopWatch
  import pytest
label_desc: Use image node_id 1 for calling a global function with example usage: test_smbo_metalearning_configurations(backend, context, dask_client) without return types